Apparatus and Methods of Evaluating Rock Properties While Drilling Using Acoustic Sensors Installed in the Drilling Fluid Circulation System of a Drilling Rig

ABSTRACT

Apparatus and methods of identifying rock properties in real-time during drilling, are provided. An apparatus includes an acoustic sensor installed in a drilling fluid circulation system of a drilling rig, the acoustic sensor coupled to one of the following: (i) a bell nipple, (ii) a gooseneck, or (iii) a standpipe. Raw acoustic sensor data generated real-time as a result of rotational contact of the drill bit with rock during drilling is received, and a plurality of acoustic characteristics are derived from the raw acoustic sensor data. The lithology type of rock undergoing drilling may be determined from the acoustic characteristics. Petrophysical properties of the rock undergoing drilling may be determined using a petrophysical properties evaluation algorithm employable to predict the petrophysical properties of rock undergoing drilling from the raw acoustic sensor data.

RELATED APPLICATIONS

This application is a continuation-in-part of and claims priority to andthe benefit of U.S. Non-Provisional patent application Ser. No.13/554,369 titled “Methods Of Evaluating Rock Properties While DrillingUsing Downhole Acoustic Sensors And A Downhole Broadband TransmittingSystem” filed on Jul. 20, 2012, which is a non-provisional of and claimspriority to and the benefit of U.S. Provisional Patent Application No.61/539,171, titled “Methods Of Evaluating Rock Properties While DrillingUsing Downhole Acoustic Sensors And A Downhole Broadband TransmittingSystem,” filed on Sep. 26, 2011, and is related to U.S. patentapplication Ser. No. 13/554,019, filed on Jul. 20, 2012, titled“Apparatus, Computer Readable Medium and Program Code for EvaluatingRock Properties While Drilling Using Downhole Acoustic Sensors andTelemetry System”; U.S. patent application Ser. No. 13/553,958, filed onJul. 20, 2012, titled “Methods of Evaluating Rock Properties WhileDrilling Using Downhole Acoustic Sensors and Telemetry System”; U.S.patent application Ser. No. 13/554,298, filed on Jul. 20, 2012, titled“Apparatus for Evaluating Rock Properties While Drilling Using DrillingRig-Mounted Acoustic Sensors”; and U.S. patent application Ser. No.13/554,470, filed on Jul. 20, 2012, titled “Methods for Evaluating RockProperties While Drilling Using Drilling Rig-Mounted Acoustic Sensors”;U.S. patent application Ser. No. 13/554,077, filed on Jul. 20, 2012,titled “Apparatus, Computer Readable Medium, and Program Code ForEvaluating Rock Properties While Drilling Using Downhole AcousticSensors and a Downhole Broadband Transmitting System; U.S. ProvisionalPatent Application No. 61/539,165, titled “Apparatus And Program ProductFor Evaluating Rock Properties While Drilling Using Downhole AcousticSensors And A Downhole Broadband Transmitting System,” filed on Sep. 26,2011; U.S. Provisional Patent Application No. 61/539,201, titled“Apparatus For Evaluating Rock Properties While Drilling Using DrillingRig-Mounted Acoustic Sensors,” filed on Sep. 26, 2011; U.S. ProvisionalPatent Application No. 61/539,213, titled “Methods For Evaluating RockProperties While Drilling Using Drilling Rig-Mounted Acoustic Sensors,”filed on Sep. 26, 2011; U.S. Provisional Patent Application No.61/539,242 titled “Apparatus And Program Product For Evaluating RockProperties While Drilling Using Downhole Acoustic Sensors And TelemetrySystem,” filed on Sep. 26, 2011; and U.S. Provisional Patent ApplicationNo. 61/539,246 titled “Methods Of Evaluating Rock Properties WhileDrilling Using Downhole Acoustic Sensors And Telemetry System,” filed onSep. 26, 2011, each incorporated herein by reference in its entirety forpurposes of United States patent Practice.

BACKGROUND OF THE INVENTION Field of the Invention

This invention relates in general to hydrocarbon production, and moreparticularly, to identifying rock types and rock properties in order toimprove or enhance drilling operations.

Description of the Related Art

Measuring rock properties during drilling in real time can provide theoperator the ability to steer a drill bit in the direction of desiredhydrocarbon concentrations. In current industrial practice and priorinventions, either resistivity or sonic logging while drilling (LWD)tools are employed to guide the drill bit during horizontal or lateraldrilling. The center of these techniques is to calculate the locationsof the boundary between the pay zone and the overlying rock (upperboundary), and the boundary between the pay zone and underlying rock(lower boundary) at the sensors location. The drill bit is steered ormaintained within the pay zone by keeping the drill string, at thesensors position, in the middle, or certain position between the upperand lower boundaries of the pay zone. The conventional borehole acoustictelemetry system, which transmits data at low rate (at about tens bitper second), is employed to transmit the measured data to surface.

Since the sensors are located 30-50 feet behind the drill bit, thesesconventional LWD steering tools only provide data used in steering thedrill bit 30-50 feet behind the drill bit. As the result, it is onlyafter the 30-50 feet that the operator finds out if the selecteddrilling path is or is not the desired one. Therefore, these tools arenot true real-time tools.

Some newer types of systems attempt to provide data at the drill bit,at-real-time, while still utilizing conventional borehole telemetrysystems (having a relatively slow bit rate). Such systems, for example,are described as including a downhole processor configured to providedownhole on-site processing of acoustic data to interpret the lithologicproperties of the rock encountered by the drill bit through comparisonof the acoustic energy generated by the drill bit during drilling withpredetermined bit characteristics generated by rotating the drill bit incontact with a known rock type. The lithologic properties interpretedvia the comparison are then transmitted to the surface via theconventional borehole telemetry system. Although providing data in areduced form requiring only a bit rate speed, as such systems do notprovide raw data real-time which can be used for further analysis, it isnearly impossible to construct additional interpretation models ormodify any interpretation models generated by the downhole processor.

Some newer types of borehole data transmitting systems utilize adedicated electronics unit and a segmented broadband cable protected bya reinforced steel cable positioned within the drill pipe to provide amuch faster communication capability. Such systems have been employedinto conventional LWD tools to enhance the resolution of the loggedinformation. However the modified tools still measures rock propertiesat the similar location which is 30-50 feet behind the drill bit.

Accordingly, recognized by the inventor is the need for apparatus,computer readable medium, program code, and methods of identifying rockproperties in real-time during drilling, and more particularly, methodswhich include positioning acoustic sensors adjacent the drill bit todetect drill sounds during drilling operations, pushing raw acousticsensor data to a surface computer over a broadband transmitting system,receiving the raw acoustic sensor data, and deriving the rock typeand/or evaluating the properties of the rocks in real-time utilizing theraw acoustic sensor data. Additionally, recognized by the inventor isthe need for apparatus, computer readable media, program code, andmethods of identifying rock properties in real-time during drilling and,more particularly, apparatus and methods which include acoustic sensorslocated in a drilling fluid circulation system of a drilling rig todetect an acoustic signal generated real-time as a result of rotationalcontact of a drill bit with rock during drilling and transmitted throughthe drilling fluid (for example, drilling mud) circulation system. Theapparatus and method include a data acquisition unit to sample the rawacoustic sensor data, and a computer to determine the lithology type ofrock or evaluate the petrophysical properties of the rocks in real-timeutilizing the raw acoustic sensor data.

SUMMARY OF THE INVENTION

In view of the foregoing, various embodiments of the present inventionadvantageously provide apparatus, computer readable medium, programcode, and methods of identifying rock types and rock properties of rockthat is currently in contact with an operationally employed drillingbit, which can be used in real-time steering of the drilling bit duringdrilling. Various embodiments of the present invention provide apparatusand methods which include acoustic sensors located in a drilling fluidcirculation system of a drilling rig to detect an acoustic signalgenerated real-time as a result of rotational contact of a drill bitwith rock during drilling and transmitted through the drilling fluid.The apparatus and method include a data acquisition unit for to samplethe raw acoustic sensor data, and a computer to identify the lithologytype of rock or evaluate the petrophysical properties of the rocks inreal-time utilizing the raw acoustic sensor data. One or more acousticsensors may be coupled to the bell nipple, gooseneck, standpipe, othercomponents, or any combination thereof of the drilling fluid circulationsystem.

According to various embodiments of the present invention, a surfacecomputer/processor receives the raw acoustic sensor data from acousticsensors. Utilizing the raw acoustic sensor data, the computer canadvantageously function to derive a frequency distribution of theacoustic sensor data, derive acoustic characteristics from the rawacoustic data, and determine petrophysical properties of rock from theraw acoustic sensor data. The acoustic characteristics canadvantageously further be used to identify the lithology type of therock encountered by the drill bit, to determine the formation boundary,to determine an optimal location of the casing shoe, among otherapplications. According to various embodiments of the present invention,to determine petrophysical properties of the rock directly from the rawacoustic sensor data (generally after being converted into the frequencydomain and filtered), a petrophysical properties evaluation algorithmcan be derived from acoustic sensor data and correspondent petrophysicalproperties of formation samples.

Various embodiments of a method of identifying rock properties of rockin real-time during operational drilling, to include identifyinglithology type and other petrophysical properties, can include thedeployment, installation, and/or positioning of both conventionalcomponents and additional/enhanced acoustic components. Some primaryconventional components include a drill string containing a plurality ofdrill pipes each having an inner bore, a drill bit connected to thedownhole end of the drill string, and a top drive system for rotatingthe drill string having both rotating and stationary portion. Theadditional/acoustic components can include a downhole sensor subassemblyconnected to and between the drill bit and the drill string, acousticsensors (e.g. accelerometer, measurement microphone, contact microphone,hydrophone) attached to or contained within the downhole sensorsubassembly adjacent the drill bit and positioned to detect drill soundsduring drilling operations. The additional components can also include abroadband transmitting system operably extending through the inner boreof each of the plurality of drill pipes and operably coupled to theacoustic sensors through the downhole data transmitting interfaceposition therewith, a surface data transmitting interface typicallyconnected to a stationary portion of the top drive system, a surfacedata acquisition unit connected to the surface data transmittinginterface, and a surface computer operably coupled to the downhole datatransmitting interface through the data acquisition unit, the surfacedata transmitting interface, and the broadband transmitting system.

Various embodiments of the method can also include both computeremployable steps (operations), as described later with respect to theoperations performed by various featured apparatus/program code, andvarious non-computer implemented steps which provide substitutablereplacements for the featured computer implemented steps, in conjunctionwith additional non-computer implemented steps as described below and/oras featured in the appended claims. Examples of various embodiments ofthe method are described below.

According to an embodiment of a method of analyzing properties of rockin a formation in real-time during drilling, the method can include thesteps of sending sampling commands to the data acquisition unit andreceiving raw acoustic sensor data from a surface data interface incommunication with a communication medium further in communication witha downhole data interface operably coupled to a plurality of acousticsensors. The method can also include various processing steps whichinclude deriving a frequency distribution of the raw acoustic sensordata, deriving a plurality of acoustic characteristics including meanfrequency and normalized deviation of frequency from the raw acousticsensor data utilizing, for example, an acoustics characteristicsevaluation algorithm, and/or deriving petrophysical properties from theraw acoustic sensor data utilizing, for example, a petrophysicalproperties evaluation algorithm employable to predict one or morepetrophysical properties of rock undergoing drilling.

According to an embodiment of the method, the step of deriving afrequency distribution of the acoustic data from the raw acoustic sensordata includes transforming the raw acoustic sensor data into thefrequency domain (e.g., employing a Fast Fourier Transform (FFT)), andfiltering the transformed data.

According to an embodiment of the method, the step of deriving theplurality of acoustic characteristics from the raw acoustic sensor datacan include providing the acoustic characteristics evaluation algorithmand comparing the mean frequency, the normalized deviation of frequency,the mean amplitude, the normalized deviation of amplitude, and apparentpower for the rock undergoing drilling with the mean frequency,normalized deviation of frequency, mean amplitude, normalized deviationof amplitude, and apparent power for a plurality of rock samples havingdifferent known lithologies according to a first configuration, orcomparing only part of the acoustic characteristics, such as the meanfrequency and the normalized deviation of frequency of the rockundergoing drilling with the same type of acoustic characteristics of aplurality of rock samples having different known lithologies accordingto another configuration. The method can also include identifyinglithology type of the rock undergoing drilling, determining a locationof a formation boundary encountered during drilling, and/or identifyingan ideal location for casing shoe positioning, among others.

According to an exemplary implementation, the mean frequency andnormalized deviation of frequency are examined together to determine anamount of correlation of the acoustic characteristics associated withthe rock undergoing drilling and the acoustic characteristics associatedwith the rock samples. Also or alternatively, the mean frequency and themean amplitude can be examined together and/or with normalized deviationof frequency and/or normalized deviation of amplitude and apparentpower, or a combination thereof. The step of comparing can beneficiallybe performed substantially continuously during drill bit steering inorder to provide enhanced steering ability.

According to an embodiment of the method, the step of derivingpetrophysical properties from the raw sensor data can include deriving abit-specific petrophysical properties evaluation algorithm for use inevaluating the received signals. The derivation of the algorithm caninclude collecting petrophysical properties data describing one or morepetrophysical properties of rock for a plurality of formation samplesand correspondent acoustic data for a preselected type of drill bit andprocessing the collected acoustic data to produce filtered FFT data. Thealgorithm derivation can also include determining one or morerelationships between features of the filtered FFT data andcorrespondent one or more petrophysical properties of rock describingpetrophysical properties of a plurality of formation samples, e.g.,utilizing mathematical modeling techniques such as, multiple regressionanalysis, artificial neural network modeling, etc. The algorithmderivation can also include coding the determined relationships intocomputer program code defining the bit-specific petrophysical propertiesevaluation algorithm. The derived algorithm can then be used inpredicting one or more petrophysical properties of the rock undergoingdrilling real-time responsive to filtered data associated with rawacoustic sensor data produced in response to the drilling.

According to another embodiment of the method, the step of derivingpetrophysical properties from the raw sensor data can also oralternatively include deriving a bit-independent petrophysicalproperties evaluation algorithm. The derivation of the algorithm caninclude collecting petrophysical properties data describing one or morepetrophysical properties of rock for a plurality of formation samplesand correspondent acoustic data for a plurality of different types ofdrill bits, processing the collected acoustic data to produce filteredFFT data, and determining bit-type independent features of the filteredFFT data. The algorithm derivation can also include determining one ormore relationships between the bit-type independent features of thefiltered FFT data and correspondent one or more petrophysical propertiesof the rock, e.g., using mathematical modeling techniques, such asartificial neural network modeling, etc., to provide a bit-independentevaluation methodology. The algorithm derivation can also include codingthe determined relationships into computer program code defining thebit-independent petrophysical evaluation properties algorithm.Correspondingly, the method can include employing the derivedpetrophysical properties evaluation algorithm to predict one or morepetrophysical properties of the rock undergoing drilling real-timeresponsive to filtered data associated with raw acoustic sensor dataproduced in response to the drilling.

According to various embodiments of the present invention, apparatus foranalyzing properties of rock in a formation in real-time during drillingare also provided. An example of an embodiment of such an apparatus caninclude a drill string containing a plurality of drill pipes each havingan inner bore, a drill bit connected to the downhole end of the drillstring, and a top drive system for rotating the drill string having bothrotating and stationary portion. The apparatus can also include adownhole sensor subassembly connected to a rotating portion of thesystem, such as, for example, to and between the drill bit and the drillstring, acoustic sensors (e.g. accelerometer, measurement microphone,contact microphone, hydrophone) attached to or contained within thedownhole sensor subassembly adjacent the drill bit and positioned todetect drill sounds during drilling operations. The apparatus canfurther include a broadband transmitting system operably extendingthrough the inner bore of each of the plurality of drill pipes andoperably coupled to the acoustic sensors through the downhole datatransmitting interface position therewith, a surface data transmittinginterface typically connected to a stationary portion of the top drivesystem, a data acquisition unit in communication with the surface datatransmitting interface, and a surface computer operably coupled to thedownhole data transmitting interface through surface acquisition unit,the surface data transmitting interface, and the broadband transmittingsystem.

According to an embodiment of the apparatus, the computer includes aprocessor, memory in communication with the processor, and petrophysicalproperties analyzing program, which can adapt the computer to performvarious operations. The operations can include, for example, sendingsampling commands to the data acquisition unit, receiving raw acousticdata from the downhole data transmitting interface, processing thereceived raw acoustic sensor data—deriving a frequency distribution ofthe acoustic data from the raw acoustic data, employing an acousticscharacteristics evaluation algorithm to thereby derive acousticcharacteristics from the raw acoustic sensor data (e.g., via analysis ofthe processed acoustics data), and employing a petrophysical propertiesevaluation algorithm to thereby derive petrophysical properties of rockundergoing drilling, real-time, from the acoustics data.

According to an embodiment of the apparatus, the acousticcharacteristics evaluation algorithm evaluates filtered Fast FourierTransform data for acoustic characteristics. The acousticcharacteristics can include mean frequency, normalized deviation offrequency, mean amplitude, normalized deviation of amplitude, andapparent power. These characteristics can be predetermined for rocksamples having a known lithology type and/or petrophysical properties,and thus, can be used to identify lithology type and other properties bycomparing such characteristics of the acoustic data received duringdrilling to that determined for the rock samples. According to anotherembodiment of the apparatus, the computer uses the derived acousticcharacteristics to determine formation boundaries based on real-timedetection of changes in the lithology type of the rock being drilledand/or petrophysical properties thereof.

According to an exemplary configuration, the petrophysical propertiesanalyzing program or separate program code functions derive a “bitspecific” or “bit independent” petrophysical properties evaluationalgorithm. Similarly, the derived bit specific or bit independentpetrophysical properties evaluation algorithm evaluates filtered FastFourier Transform data for petrophysical properties. This petrophysicalproperty data can advantageously be applied by other applications toinclude real-time formation boundary determination, casing shoe positionfine-tuning, geosteering, etc.

According to an embodiment of the present invention, the petrophysicalproperties analyzing program can be provided either as part of theapparatus or as a standalone deliverable. As such, the petrophysicalproperties analyzing program can include a set of instructions, storedor otherwise embodied on a non-transitory computer readable medium, thatwhen executed by a computer, cause the computer to perform variousoperations. These operations can include the operation of receiving rawacoustic sensor data from a surface data interface in communication witha communication medium that is further in communication with a downholedata interface operably coupled to a plurality of acoustic sensors. Theoperations can also include the processing operations of deriving afrequency distribution of the raw acoustic sensor data, deriving aplurality of acoustic characteristics including mean frequency andnormalized deviation of frequency from the raw acoustic sensor data,and/or deriving petrophysical properties from the raw acoustic sensordata utilizing a derived petrophysical properties evaluation algorithmemployable to predict one or more petrophysical properties of rockundergoing drilling.

According to an embodiment of the petrophysical properties analyzingprogram, the operation of deriving a frequency distribution of theacoustic data from the raw acoustic sensor data includes transformingthe raw acoustic sensor data into the frequency domain (e.g., employinga Fast Fourier Transform), and filtering the transformed data.

According to an embodiment of the petrophysical properties analyzingprogram, the operation of deriving the plurality of acousticcharacteristics from the raw acoustic sensor data can include comparingthe mean frequency, the normalized deviation of frequency, the meanamplitude, the normalized deviation of amplitude, and apparent power forthe rock undergoing drilling with the mean frequency, normalizeddeviation of frequency, mean amplitude, normalized deviation ofamplitude, and apparent power for a plurality of rock samples havingdifferent known lithologies according to a first configuration, orcomparing only part of the acoustic characteristics, such as the meanfrequency and the normalized deviation of frequency of the rockundergoing drilling with the same type of acoustic characteristics of aplurality of rock samples having different known lithologies accordingto another configuration. The operations can also include identifyinglithology type of the rock undergoing drilling, determining a locationof a formation boundary encountered during drilling, and/or identifyingan ideal location for casing shoe positioning, among others.

According to an exemplary implementation, the mean frequency andnormalized deviation of frequency are examined together to determine anamount of correlation of the acoustic characteristics associated withthe rock undergoing drilling and the acoustic characteristics associatedwith the rock samples. Also or alternatively, the mean frequency and themean amplitude can be examined together and/or with the normalizeddeviation of frequency or apparent power, or a combination thereof. Theoperation of comparing can beneficially be performed substantiallycontinuously during drill bit steering in order to provide enhancedsteering ability.

According to an embodiment of the petrophysical properties analyzingprogram employing a bit-specific evaluation methodology, the operationof deriving petrophysical properties from the raw acoustic sensor datacan include deriving a bit-specific petrophysical properties evaluationalgorithm. The derivation of the algorithm can include collectingpetrophysical properties data describing one or more petrophysicalproperties of rock for a plurality of formation samples andcorrespondent acoustic data for a preselected type of drill bit,processing the collected acoustic data to produce filtered FFT data, anddetermining one or more relationships between features of the filteredFFT data and correspondent one or more petrophysical properties of rockdescribing petrophysical properties of the plurality of formationsamples. This can be accomplished, for example, by utilizingmathematical modeling techniques such as, multiple regression analysis,artificial neural network modeling, etc. The derivation of the algorithmcan also include coding the determined relationships into computerprogram code defining the petrophysical properties evaluation algorithm.The operations can correspondingly include employing the derivedpetrophysical properties evaluation algorithm to predict one or morepetrophysical properties of the rock undergoing drilling real-timeresponsive to filtered data associated with raw acoustic sensor dataproduced in response to the drilling.

According to an embodiment of the petrophysical properties analyzingprogram employing a bit-independent evaluation methodology, thepetrophysical properties evaluation algorithm derivation can also oralternatively include collecting petrophysical properties datadescribing one or more petrophysical properties of rock for a pluralityof formation samples and correspondent acoustic data for a plurality ofdifferent types of drill bits, processing the collected acoustic data toproduce filtered FFT data, determining bit-type independent features ofthe filtered FFT data, and determining one or more relationships betweenthe bit-type independent features of the filtered FFT data andcorrespondent one or more petrophysical properties of the rock toprovide a bit-independent evaluation methodology. The algorithmderivation can also include coding the determined relationships intocomputer program code defining a bit-independent petrophysicalproperties evaluation algorithm. The operations can correspondinglyinclude employing the derived bit-independent petrophysical propertiesevaluation algorithm to predict one or more petrophysical properties ofthe rock undergoing drilling real-time responsive to filtered dataassociated with raw acoustic sensor data produced in response to thedrilling.

According to another embodiment, an apparatus for determining propertiesof rock in a formation in real-time during drilling includes an acousticsensor installed in a drilling fluid circulation system of a drillingrig and coupled to one of the following: (i) a bell nipple, (ii) agooseneck, or (iii) a standpipe. The acoustic sensor is operable todetect an acoustic signal generated real-time as a result of rotationalcontact of a drill bit with rock during drilling and transmitted throughthe drilling fluid. The apparatus includes a data acquisition unit incommunication with the acoustic sensor and a computer. The dataacquisition unit is operable to sample the raw acoustic sensor data anddigitize the raw acoustic sensor data. The computer is in communicationwith the acoustic sensor and configured to perform the operations thatinclude receiving digitized acoustic sensor data from the dataacquisition unit, the raw acoustic sensor data representing the acousticsignal generated real-time as a result of rotational contact of a drillbit with rock during drilling, and processing the digitized acousticsensor data received from the acoustic sensor. The processing includesderiving a plurality of acoustic characteristics from the digitizedacoustic sensor data, the plurality of acoustic characteristicsincluding mean frequency and normalized deviation of frequency andcomparing the mean frequency and the normalized deviation of frequencyfor the rock undergoing drilling with mean frequency and normalizeddeviation of frequency for a plurality of rock samples having differentknown lithologies. The computer is configured to perform operations thatfurther include identifying a lithology type of the rock undergoingdrilling responsive to the comparing. In some embodiments, the pluralityof acoustic characteristics further include mean amplitude, normalizeddeviation of amplitude, and apparent power, and the operations includecomparing the mean frequency, the normalized deviation of frequency, themean amplitude, and the normalized deviation of amplitude, and theapparent power for the rock undergoing drilling with mean frequency,normalized deviation of frequency, mean amplitude, normalized deviationof amplitude, and apparent power for a plurality of rock samples havingdifferent known lithologies. In some embodiments, the processingincludes sending sampling commands to the data acquisition unit incommunication with the one or more acoustic sensors, converting analogacoustic signals into digitized data through employment of the dataacquisition unit, transforming the digitized data into Fast FourierTransform data using a Fast Fourier transformation, filtering the FastFourier Transform data, restoring the Fast Fourier Transform data tocompensate for attenuation by the drilling fluid, and deriving theplurality of acoustic characteristics from the filtered and restoredFast Fourier Transform data. In some embodiments, the apparatus includesan amplifier connected to the acoustic sensor, the amplifier is operableto amplify the raw acoustic sensor data before received by the dataacquisition unit. In some embodiments, the acoustic sensor includes afirst acoustic sensor installed in coupled to the bell nipple of thedrilling fluid circulation system. In some embodiments, the acousticsensor includes a second acoustic sensor coupled to the gooseneck of thedrilling fluid circulation system. In some embodiments, the acousticsensor includes a third acoustic sensor coupled to the standpipe of thedrilling fluid circulation system.

According to another embodiment, an apparatus for determining propertiesof rock in a formation in real-time during drilling includes an acousticsensor installed in a drilling fluid circulation system of a drillingrig and coupled to one of the following: (i) a bell nipple, (ii) agooseneck, or (iii) a standpipe. The acoustic sensor is operable todetect an acoustic signal generated real-time as a result of rotationalcontact of a drill bit with rock during drilling and transmitted throughthe drilling fluid. The apparatus includes a data acquisition unit incommunication with the acoustic sensor and a computer. The dataacquisition unit is operable to sample the raw acoustic sensor data anddigitize the raw acoustic sensor data. The computer is in communicationwith the acoustic sensor and configured to perform the operations thatinclude receiving digitized acoustic sensor data from the dataacquisition unit, the raw acoustic sensor data representing the acousticsignal generated real-time as a result of rotational contact of a drillbit with rock during drilling, and processing the raw acoustic sensordata received from the acoustic sensor. The processing includestransforming the digitized data into Fast Fourier Transform (FFT) datausing a Fast Fourier transformation, filtering the FFT data, restoringthe FFT data to compensate for attenuation by the drilling fluid, anddetermining petrophysical properties of rock being encountered by thedrill bit using a petrophysical properties evaluation algorithmemployable to predict one or more petrophysical properties of rockundergoing drilling using the filtered and restored FYI data. In someembodiments, the apparatus includes an amplifier connected to theacoustic sensor, such that the amplifier is operable to amplify the rawacoustic sensor data before received by the data acquisition unit. Insome embodiments, the processing includes sending sampling commands tothe data acquisition unit in communication with the one or more acousticsensors and converting analog acoustic signals into digitized datathrough employment of the data acquisition unit. In some embodiments,the one or more petrophysical properties include: lithology type,porosity, water saturation, and permeability of rock undergoingdrilling. In some embodiments, the petrophysical properties evaluationalgorithm is a bit-specific petrophysical properties evaluationalgorithm and the processing includes collecting petrophysicalproperties data describing one or more petrophysical properties of rockcontained in a data set and correspondent acoustic data for apreselected type of drill bit, processing the collected acoustic data toproduce filtered and restored FFT data, determining one or morerelationships between features of the filtered and restored FFT data andcorrespondent one or more petrophysical properties of rock for each typeof drill bit, and coding the determined relationships into computerprogram code defining the petrophysical properties algorithm. In someembodiments, the petrophysical properties evaluation algorithm is abit-independent petrophysical properties evaluation algorithm and theprocessing includes collecting petrophysical properties data describingone or more petrophysical properties of rock and correspondent acousticdata for a plurality of different types of drill bits, processing thecollected acoustic data to produce filtered and restored FFT data,determining bit-type independent features of the filtered and restoredFFT data, determining one or more relationships between the bit-typeindependent features of the filtered and restored FFT data andcorrespondent one or more petrophysical properties of the rock, andcoding the determined relationships into computer program code definingthe petrophysical properties algorithm. In some embodiments, theacoustic sensor includes a first acoustic sensor coupled to the bellnipple of the drilling fluid circulation system. In some embodiments,the acoustic sensor includes a second acoustic sensor coupled to thegooseneck of the drilling fluid circulation system. In some embodiments,the acoustic sensor includes a third acoustic sensor coupled to thestandpipe of the drilling fluid circulation system.

According to another embodiment, a method for determining properties ofrock in a formation in real-time during drilling using a drilling fluidincludes detecting, by an acoustic sensor, an acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling and transmitted through the drilling fluid, the acousticsensor installed in a drilling fluid circulation system of a drillingrig and coupled to one of the following: (i) a bell nipple, (ii) agooseneck, or (iii) a standpipe. The method includes digitizing, by adata acquisition unit, the raw acoustic sensor data and processing, at acomputer in communication with the data acquisition unit, the digitizedacoustic sensor data received from the acoustic sensor. The processingincludes deriving a plurality of acoustic characteristics from thedigitized acoustic sensor data, the plurality of acousticcharacteristics including mean frequency and normalized deviation offrequency and comparing the mean frequency and the normalized deviationof frequency for the rock undergoing drilling with mean frequency andnormalized deviation of frequency for a plurality of rock samples havingdifferent known lithologies. The method also includes identifying alithology type of the rock undergoing drilling responsive to thecomparing. In some embodiments, the method includes sending samplingcommands to the data acquisition unit in communication with the one ormore acoustic sensors, converting analog acoustic signals into digitizeddata through employment of the data acquisition unit, transforming thedigitized data into FFT data using a Fast Fourier transformation,filtering the FFT data, restoring the FFT data to compensate forattenuation by the drilling fluid, and deriving the plurality ofacoustic characteristics from the filtered and restored FFT data. Insome embodiments, the method includes amplifying the raw acoustic sensordata by an amplifier before being received by the data acquisition unit.In some embodiments, the plurality of acoustic characteristics furtherinclude mean amplitude, normalized deviation of amplitude, and apparentpower and the method includes comparing the mean frequency, thenormalized deviation of frequency, the mean amplitude, the normalizeddeviation of amplitude, and the apparent power for the rock undergoingdrilling with mean frequency, normalized deviation of frequency, meanamplitude, normalized deviation of amplitude, and apparent power for aplurality of rock samples having different known lithologies. In someembodiments, the method includes determining a location of a formationboundary encountered during drilling responsive to the comparing. Insome embodiments, the method includes determining an optimal location ofa casing shoe for a casing associated with a drill string based on thelocation of the formation boundary. In some embodiments, the acousticsensor includes a first acoustic sensor coupled to the bell nipple ofthe drilling fluid circulation system. In some embodiments, the acousticsensor includes a second acoustic sensor coupled to the gooseneck of thedrilling fluid circulation system. In some embodiments, the acousticsensor includes a third acoustic sensor coupled to the standpipe of thedrilling fluid circulation system.

According to another embodiment, a method for determining properties ofrock in a formation in real-time during drilling using a drilling fluidincludes detecting, by an acoustic sensor, an acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling and transmitted through the drilling fluid, the acousticsensor installed in a drilling fluid circulation system of a drillingrig and coupled to one of the following: (i) a bell nipple, (ii) agooseneck, or (iii) a standpipe. The method includes digitizing, by adata acquisition unit, the raw acoustic sensor data and processing, at acomputer in communication with the data acquisition unit, the digitizedacoustic sensor data received from the acoustic sensor. The processingincludes transforming the digitized data into Fast Fourier Transform(FFT) data using a Fast Fourier transformation, filtering the FFT data,restoring the FFT data to compensate for attenuation by the drillingfluid, and determining petrophysical properties of rock beingencountered by the drill bit using a petrophysical properties evaluationalgorithm employable to predict one or more petrophysical properties ofrock undergoing drilling using the filtered and restored FFT data. Insome embodiments, the method includes amplifying the raw acoustic sensordata by an amplifier before the being received by the data acquisitionunit. In some embodiments, the one or more petrophysical propertiesinclude: lithology type, porosity, water saturation, and permeability ofrock undergoing drilling. In some embodiments, the petrophysicalproperties evaluation algorithm is a bit-specific petrophysicalproperties evaluation algorithm and the method includes collectingpetrophysical properties data describing one or more petrophysicalproperties of rock contained in a data set and correspondent acousticdata for a preselected type of drill bit, processing the collectedacoustic data to produce filtered and restored FFT data, determining oneor more relationships between features of the filtered and restored FFTdata and correspondent one or more petrophysical properties of rock foreach type of drill bit, and coding the determined relationships intocomputer program code defining the petrophysical properties algorithm.In some embodiments, the petrophysical properties evaluation algorithmis a bit-independent petrophysical properties evaluation algorithm andthe method includes collecting petrophysical properties data describingone or more petrophysical properties of rock and correspondent acousticdata for a plurality of different types of drill bits, processing thecollected acoustic data to produce filtered and restored FFT data,determining bit-type independent features of the filtered and restoredFFT data, determining one or more relationships between the bit-typeindependent features of the filtered and restored FFT data andcorrespondent one or more petrophysical properties of the rock, andcoding the determined relationships into computer program code definingthe petrophysical properties algorithm. In some embodiments, the methodincludes determining a location of a formation boundary encounteredduring drilling based on the determined petrophysical properties of therock undergoing drilling. In some embodiments, the method includesdetermining an optimal location of a casing shoe for a casing associatedwith a drill string based on the location of the formation boundary. Insome embodiments, the acoustic sensor includes a first acoustic sensorcoupled to the bell nipple of the drilling fluid circulation system. Insome embodiments, the acoustic sensor includes a second acoustic sensorcoupled to the gooseneck of the drilling fluid circulation system. Insome embodiments, the acoustic sensor includes a third acoustic sensorcoupled to the standpipe of the drilling fluid circulation system.

Various embodiments of the present invention advantageously supply a newapproach for a much better drilling steering. Various embodiments of thepresent invention provide apparatus and methods that supply detailedinformation about the rock that is currently in contact with thedrilling bit, which can be used in real-time steering the drilling bit.That is, various embodiments of the present invention advantageouslyprovide an employable methodology of retrieving a sufficient level ofinformation so that the driller always knows the rock he is drilling, sothat the drilling bit can be steered to follow the desire path moreaccurately than conventionally achievable. In comparison withconventional drilling steering tools, the real-time data provided byvarious embodiments of the present invention advantageously allow thedriller to drill smoother lateral or horizontal wells with bettercontact with the production zone, to detect formation boundaries inreal-time, and to detect the fractured zones in real-time, and toperform further analysis on raw sensor data, if necessary.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the features and advantages of theinvention, as well as others which will become apparent, may beunderstood in more detail, a more particular description of theinvention briefly summarized above may be had by reference to theembodiments thereof which are illustrated in the appended drawings,which form a part of this specification. It is to be noted, however,that the drawings illustrate only various embodiments of the inventionand are therefore not to be considered limiting of the invention's scopeas it may include other effective embodiments as well.

FIGS. 1A-1B is a partial perspective view and partial schematic diagramof a general architecture of an apparatus for identifying rockproperties in real-time during drilling according to an embodiment ofthe present invention;

FIG. 2 is a schematic diagram showing a data processing procedureperformed by a computer program according to an embodiment of thepresent invention;

FIG. 3 is a schematic diagram illustrating major components of a datapreprocess module according to an embodiment of the present invention;

FIGS. 4A-4B are graphs illustrating examples of a frequency distributionof two types of carbonate according to an embodiment of the presentinvention;

FIG. 5 is a graph illustrating a three dimensional depiction of thefrequency distribution in correlation with various lithography typesaccording to an embodiment of the present invention;

FIG. 6 is a graph illustrating a comparison of mean frequency andnormalized deviation of frequency correlated with a plurality oflithology types according to an embodiment of the present invention;

FIG. 7 is a schematic flow diagram illustrating steps for forming apetrophysical properties evaluation algorithm for a particular type ofdrill bit according to an embodiment of the present invention;

FIG. 8 is a schematic flow diagram illustrating steps for forming adrill bit independent petrophysical properties evaluation algorithmaccording to an embodiment of the present invention;

FIG. 9 is a schematic diagram of a general architecture of an apparatusfor identifying rock properties in real-time during drilling accordingto another embodiment of the present invention;

FIG. 10 is a schematic diagram showing a data processing procedureperformed by a computer program according to another embodiment of thepresent invention;

FIG. 11 is a schematic diagram illustrating major components of a datapreprocess module according to another embodiment of the presentinvention;

FIG. 12 is a schematic flow diagram illustrating steps for forming apetrophysical properties evaluation algorithm for a particular type ofdrill bit according to another embodiment of the present invention; and

FIG. 13 is a schematic flow diagram illustrating steps for forming adrill bit independent petrophysical properties evaluation algorithmaccording to another embodiment of the present invention

DETAILED DESCRIPTION

The present invention will now be described more fully hereinafter withreference to the accompanying drawings, which illustrate embodiments ofthe invention. This invention may, however, be embodied in manydifferent forms and should not be construed as limited to theillustrated embodiments set forth herein. Rather, these embodiments areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the invention to those skilled in the art.Like numbers refer to like elements throughout. Prime notation, if used,indicates similar elements in alternative embodiments.

When drilling into different lithologies or the same lithology withdifferent properties (e.g., porosity, water saturation, permeability,etc.) the generated acoustic sounds emanating from the drill bit whendrilling into rock, are distinctly different. The sounds, termed asdrilling acoustic signals hereafter, transmit upward along the drillstring. According to various embodiments of the present invention, asensor subassembly containing acoustic sensors is positioned above thedrill bit and connected to the above drill string. The drilling acousticsignals transmit from the drill bit to the sensor subassembly and arepicked up by the acoustic sensors. The drilling acoustic signalsreceived by the sensors are transmitted (generally after amplification)to surface by a borehole transmitting system which can include variouscomponents such as, for example, a downhole data interface, a broadbandconductor, a surface data interface, etc. According to anotherembodiment of the present invention, acoustic sensors are positioned inthe drilling fluid circulation system. The drilling acoustic signalstransmit upwards in the drilling fluid circulation system from the drillbit to the sensors and are picked up by the acoustic sensors. Thedrilling acoustic signals received by the sensors are transmitted(generally after amplification) to a data acquisition unit (DAQ)connected with the acoustic sensors and then to a computer through adata transmitting system. On the surface, the received acoustic signalsare transformed by a data processing module into the frequency domainusing, for example, a Fast Fourier Transformation (FFT) to generate FFTdata (primarily the frequency and amplitude data). Some acousticcharacteristics are derived directly from the FFT data. The frequencydistribution and acoustic characteristics, for example, can be usedimmediately in some applications, such as lithology type identificationand formation boundary determination. The FFT data can be furtheranalyzed using a calibrated mathematical model, for the lithology typeand petrophysical properties, which have wider applications than thedirect results (frequency distribution and acoustic characteristics).

Where conventional measurement-while-drilling tools are typicallylocated 30 to 50 feet behind the drill bit, beneficially, a majoradvantage of approaches employed by various embodiments of the presentinvention is that such approaches can derive information aboutlithologies from a position located at the cutting surface of the drillbit or via acoustic signals transmitted through the drilling fluid toprovide such information to the operator steering the drill bit, in realtime. This advantage makes aspects of various embodiments of the presentinvention ideal in the application of horizontal and lateral well drillsteering, locating the relative position for setting the casing shoe,detecting fractured zones, and interpreting rock lithologies andpetrophysical properties in real time.

FIGS. 1A-1B schematically show the setup of an exemplary apparatus foridentifying rock properties in real-time during drilling 100. Acousticsensors 102 are connected to a downhole data “transmitting” interface103. According to the exemplary configuration, both are contained in asensor subassembly 104, which is positioned above a drill bit 101 andconnected to a drill string 117. In operation, the drilling acousticsignals are generated when the drill bit 101 bites rocks at the bottomof a borehole 118 during the drilling process.

Different acoustic sensors 102 may be used, e.g. accelerometer,measurement microphone, contact microphone, and hydrophone. According tothe exemplary configuration, at least one, but more typically eachacoustic sensor 102 either has a built-in amplifier or is connecteddirectly to an amplifier (not shown). The drilling acoustic signalspicked up by the acoustic sensors 102 are amplified first by theamplifier before transmitted to the downhole data interface 103.

From the downhole data interface 103, acoustic signals are transmittedto a surface data “transmitting” interface 106 through a boreholebroadband data transmitting system 105. Currently, one commerciallyavailable broadband data transmitting system, NOV™ IntelliServ®, cantransmit data at the rate of 1000,000 bit/s. A study indicated that withtwo acoustic sensors 102 at normal working sampling rate of 5 secondsper sample, the required data transmitting rate was about 41,000 bits/s.Therefore, the NOV™ IntelliServ® borehole broadband data transmittingsystem is an example of a broadband communication media capable oftransmitting acoustic signals data for at least four acoustic sensors102 to surface directly from a downhole data interface 103.

According to the exemplary configuration, the surface data interface 106is located at the stationary part of the top drive 107. From the surfacedata interface 106, the acoustic signals are further transmitted to adata acquisition unit 110 through an electronic cable 108, which isprotected inside a service loop 109. The data acquisition unit 110 isconnected to a computer 124 through an electronic cable 126. The dataacquisition unit 110 samples the acoustic signal in analog format andthen converts the analog acoustic signals into digit data in FIG. 2.

Referring to FIGS. 1 and 2, the digitized data 111 is read by a computerprogram 112 (e.g., a petrophysical properties analyzing program),installed in memory 122 accessible to processor 123 of computer 124. Thecomputer program 112 analyzes the digitized data 111 to derive afrequency distribution 113, acoustic characteristics 114, andpetrophysical properties 115 of the rock undergoing drilling. Therespective results, e.g., frequency distribution 113, acousticcharacteristics 114, and petrophysical properties 115, can be used invarious applications 116 to include lithology identification, drill bitsteering, formation boundary identification, among others. Such dataalong with rock sample data, rock modeling data, etc. can be stored indatabase 125 stored in either internal memory 122 or an external memoryaccessible to processor 123.

Note, the computer 124 can be in the form of a personal computer or inthe form of a server or server farm serving multiple user interfaces orother configurations known to those skilled in the art. Note, thecomputer program 112 can be in the form of microcode, programs,routines, and symbolic languages that provide a specific set or sets ofordered operations that control the functioning of the hardware anddirect its operation, as known and understood by those skilled in theart. Note also, the computer program 112, according to an embodiment ofthe present invention, need not reside in its entirety in volatilememory, but can be selectively loaded, as necessary, according tovarious methodologies as known and understood by those skilled in theart. Still further, at least portions of the computer program 112 can bestored in memory of the sensor subassembly 104 when so configured.

Referring to FIG. 3, according to the exemplary configuration, thedigitized data 111 needs to be preprocessed before any use. According tothe exemplary configuration, this is accomplished by a subroutineprogram referred to as data preprocess module 200. As illustrated in thefigure, the digitized data is transformed into Fast Fourier Transform(FFT) data 202 by a FFT 201. The FFT data 202 is then filtered by afilter 203 to remove some low/high frequency and/or low amplitude datapoints, generated from other sources, i.e. not from the bit cutting intothe rocks. The filtered FFT data 301 is then used in the various part ofdata process. Note the filtered FFT data 301 is relabeled as 403 inFIGS. 7 and 503 in FIG. 8. Note also, the digitized data 111 isrelabeled as 402 in FIG. 7, and 502 in FIG. 8.

Major components and functions of the computer program 112 according toan exemplary configuration are detailed in FIG. 2. According to theexemplary configuration, there are four modules (components) in thecomputer program 112: a data preprocess module 200, a data samplingmodule 210, an acoustic characteristics evaluation algorithm 302, and apetrophysical properties evaluation algorithm 303. The sampling module210 sends sampling commands 127, such as sampling rate, to the dataacquisition unit 110 for data sampling control. The main part of thefiltered FFT data 301 is a frequency distribution 113, which is thefrequency and amplitude information of a sampled acoustic signal. Twoexamples of such signal are shown in FIGS. 4A and 4B. FIG. 4Aillustrates the frequency distribution for a limestone and FIG. 4Billustrates the frequency distribution for a dolomite. A review of thefrequency distribution of the two different types of carbonatesillustrates how the frequency distribution can be used directly todistinguish lithologies.

According to the exemplary configuration, the frequency distribution 113can be used directly in some applications, such as lithology typeidentification, formation boundaries determination, etc., represented byexample at 116. The frequency distribution 113 can be plotted intodepth-frequency spectrum which can be used directly in someapplications, such as lithology type identification, formationboundaries determination, etc., represented by example at 116.

An example of such signal displaying diagram is shown in FIG. 5, whichillustrates results of a laboratory experiment showing differentlithologies have different frequency spectrums and lithology boundariescan be determined using the diagram. In FIG. 5, the color representsamplitude, with color normally displayed as red being highest (theintermixed color mostly concentrated just below the 4000 Hz range inthis example) and the color normally displayed as blue being the lowest(the more washed out color in this example).

According to the exemplary configuration, an acoustic characteristicsevaluation algorithm 302 evaluates the filtered FFT data 301 for selectacoustic characteristics, such as, for example, mean frequency,normalized deviation of frequency, mean amplitude, normalized deviationof amplitude, and apparent power. These acoustic characteristics for anacoustic signal sample are defined as follows:

$\begin{matrix}{\mu_{f} = \frac{\Sigma_{i = 1}^{n}{A_{i} \cdot f_{i}}}{\Sigma_{i = 1}^{n}A_{i}}} & (1) \\{\sigma_{f_{—}N} = {\frac{1}{\mu_{f}}\sqrt{\Sigma_{i = 1}^{n}\frac{A_{i}}{\Sigma_{i = 1}^{n}A_{i}}( {f_{i} - \mu_{f}} )^{2}}}} & (2) \\{\mu_{A} = {\frac{1}{n}\Sigma_{i = 1}^{n}A_{i}}} & (3) \\{\sigma_{A_{—}N} = {\frac{1}{\mu_{A}}\sqrt{\frac{1}{n}{\Sigma_{i = 1}^{n}( {A_{i} - \mu_{A}} )}^{2}}}} & (4) \\{P_{a} = {\Sigma_{i = 1}^{n}A_{i}^{2}f_{i}^{2}}} & (5)\end{matrix}$

wherein:

-   -   μ_(ƒ)—mean frequency, Hz,    -   σ_(ƒ) _(_) _(N)—normalized deviation of frequency, Hz,    -   μ_(A)—mean amplitude, the unit depending on the type of acoustic        sensor used in the measurement,    -   σ_(A) _(_) _(N)—normalized deviation of amplitude, the unit        depending on the type of acoustic sensor used in the        measurement,    -   P_(a)—apparent power, the unit depending on the type of acoustic        sensor used in the measurement,    -   ƒ_(i)—frequency of the i^(th) point of the acoustic signal        sample, Hz,    -   A_(i)—amplitude of the i^(th) point of the acoustic signal        sample, the unit depending on the type of acoustic sensor used        in the measurement, and    -   n—number of data points of the acoustic signal sample.

The mean frequency and the normalized deviation of frequencycharacterize the frequency distribution, while the mean amplitude andthe normalized deviation of amplitude characterize the loudness level ofthe drilling sound. Apparent power represents the power of the acousticsignals. In the evaluation, these characteristics can be calculatedwithin the whole range or a partial range of the frequency of theacoustic samples. The range is selected to achieve the maximumdifference of these characteristics among different lithologies.

The derived acoustic characteristics 114 can be used directly forcertain applications, such as lithology type identification, formationboundary determination represented by example at 116. FIG. 6 illustratesresults of a laboratory experiment showing that the mean frequency andnormalized deviation of frequency correlated well with differentlithology types.

According to an exemplary embodiment of the present invention, the meanfrequency, the normalized deviation of frequency, the mean amplitude,the normalized deviation of amplitude, and/or the apparent power of therock undergoing drilling can be compared with a corresponding meanfrequency, normalized deviation of frequency, mean amplitude, normalizeddeviation of amplitude and/or apparent power of a plurality of rocksamples having different known lithologies, to thereby determine anamount of correlation of the acoustic characteristics associated withthe rock undergoing drilling and the acoustic characteristics associatedwith the rock samples. Responsively, the lithology type of the rockundergoing drilling can be determined.

FIGS. 7 and 8 illustrate examples of the construction of two types ofpetrophysical properties evaluation algorithms 303: one designed for aparticular type of drill bit shown at 303A and the other designed to bedrill bit type independent shown at 303B. Unlike the FFT 201 and theacoustic characteristics evaluation algorithm 302, which are based onknown mathematical equations, the petrophysical properties evaluationalgorithm 303 is based on mathematical models, which are to be builtutilizing acoustic data and petrophysical properties according to anexemplary configuration.

FIG. 7 illustrates the procedure for constructing a “PetrophysicalProperties Evaluation Algorithm” for a particular type of drill bit.According to the exemplary configuration, datasets of petrophysicalproperties 401 and correspondent digitized acoustic data 402 for aparticular drill bit are collected. The digitized acoustic data 402 ispreprocessed by the data preprocess module 200 (referred to in FIG. 2)to produce the filtered FFT data 403. The relationships 405 betweenfiltered FFT data 403 and petrophysical properties 401 are constructed(step 404) using suitable mathematical modeling techniques, such as,multiple regression analysis, artificial neural networks modeling. Oncerelationships 405 between the filtered FFT data 403 and petrophysicalproperties 401 are constructed, the relationships are coded (step 406)to produce a computer program, module, subroutine, object, or other typeof instructions to define the “petrophysical properties evaluationalgorithm” 303A. The algorithm 303A is then available to be used in thecomputer program 112 to predict the petrophysical properties fromdrilling acoustic signals for the particular drill bit type.

FIG. 8 illustrates the procedure for constructing a drill bit typeindependent “Petrophysical Properties Evaluation Algorithm” 303B. Thedatasets of petrophysical properties 501 and the correspondent acousticdata 502 measured from different types of drill bit are collected. Theacoustic data 502 is preprocessed by the data preprocess module 200(e.g., the module referred to FIGS. 2 and 3) to produce the filtered FFTdata 503. Bit type independent features 505 of the filtered FFT data 503are then determined by comparing the filtered FFT data of differenttypes of drill bit and the correspondent petrophysical properties 501(step 504). Features which have weakest correlation with the drill bittypes and strong correlation with the petrophysical properties are thebit-type independent ones. The relationships 507 between thepetrophysical properties 501 and the bit type independent features 505are constructed (step 506) using suitable mathematical modelingtechniques, such as, for example, multiple regression analysis,artificial neural networks modeling, among others. The constructedrelationships 507 are then coded (step 508) into a computer program,module, subroutine, object, or other type of instructions to define the“petrophysical properties evaluation algorithm” 303B. The algorithm 303Bis then available to be used in the computer program 112 to predict thepetrophysical properties from drilling acoustic signals.

Application of the results from the processed acoustic signal.

One direct result is the frequency distribution 113 (FIG. 2), which maybe used directly in lithology type identification, formation boundarydetermination. FIGS. 4A and 4B, for example, show the frequencydistribution of two different types of carbonates. The figuresillustrate that the frequency distribution can be used in the lithologytype identification from matching a detective frequency distributionwith a frequency distribution of a rock of known lithography type.

FIG. 6 demonstrates the feasibility of using acoustic characteristics114 (FIG. 2) to derive lithology information. In FIG. 6, mean frequencyand normalized deviation were calculated from FFT data of the drillingsounds of a sample corer drilling into cores of different lithologies.The figure demonstrates how the lithology types can be distinguished bythe combination of the two characteristics: mean frequency and thenormalized deviation of frequency. If mean amplitude and the normalizeddeviation of the amplitude are also used, an even better result may beachieved. The figure also inherently demonstrates that formationboundaries can be determined from acoustic characteristics. FIGS. 7 and8 demonstrate the feasibility of building a petrophysical propertiesevaluation algorithm 303 (FIG. 2) which can be used to evaluateprocessed forms of the sound generated by operationally engaging thedrilling bit with the rock being drilled.

In some embodiments, acoustic sensors may be installed in a drillingfluid circulation system of a drilling rig to record acoustic drillingsignals in real-time. The drill sounds, termed as drilling acousticsignals, may transmit toward the surface along the drilling fluid bothinside the drill string and the annulus to be recorded by the acousticsensors located in the drilling fluid circulation system. The recordeddrilling acoustic signals are processed and analyzed to determinelithology type and petrophysical properties of the rock under drillingin real time. The determined real time lithology type and petrophysicalproperties may be used in various applications, such as steering a drillbit (geosteering), casing shoe positioning, etc.

FIG. 9 depicts the setup of an example apparatus 900 for identifyingrock properties in real-time during drilling. The apparatus 900 may beattached to a drilling rig 902. As will be appreciated, the drilling rig902 may be a top drive drilling rig or a rotary table drilling rig.Embodiment of the apparatus 900 described in the disclosure may be usedwith a top drive drilling rig, a rotary table drilling rig, or any othertype of drilling rig in which drilling fluid (for example, drilling mud)is used to circulate drilling cuttings out of the well. FIG. 9 depictssome components of a drilling rig that may be applicable to numeroustypes of drilling rigs and are thus illustrative of embodiments of theapparatus 900.

As will be appreciated, drilling of a well is achieved by the rotationalaction of a drill bit 904. The drill bit 904 is connected to a downholeend of a drill string 906. In a top drive drilling rig, the rotationalaction of the drill bit 904 is achieved by a top drive 908 that rotatesthe drill string 906. The top drive 908 of the drilling rig 902 may besuspended in a derrick 910 by a traveling block 912. The derrick 910 issupported on a rig floor 914.

A drive shaft 916 is located in the center of the top drive 908 and maybe connected to the top pipe of the drill string 906 via a threadedconnection. The drill string 906 runs through a bell nipple 918, ablowout preventer (BOP) 920, and a casing head 922. The rotation of thetop drive 908 rotates the drive shaft 916, causing rotation of the drillstring 906 and the drill bit 904 to cut rock at the bottom of a borehole924. As will be appreciated, a rotary table drilling rig may rotate adrill string via the coupling between a kelly drive 926 and a rotarytable 928.

During drilling, the produced cuttings from drilling (for example, smallrock fragments broken by the drill bit) are carried to the surface by adrilling fluid 930. As will be appreciated, the drilling fluid 930 mayprovide multiple functions, including exerting a hydrostatic pressuresufficient to prevent formation fluids from entering the borehole 924and to keep the borehole 924 stable.

The drilling fluid 930 may be circulated by a drilling fluid circulationsystem. For example, the drilling fluid 930 may be pumped from adrilling fluid reserve pit 932 by pumps 934, and the drilling fluidcirculation system may include various components for controlling androuting the drilling fluid. For example, the drilling fluid may bepumped through a flowline 936, a standpipe 938, a kelly hose 940, agooseneck 942, a wash pipe assembly (not shown) for a top drive drillingrig, the drive shaft 916, a swivel (not shown) and the kelly drive 926for a rotary table drilling rig, and down the drill string 906. At thebottom of the borehole 924 the drilling fluid flows through the drillbit 904 and then up the annulus 944, the casing head 922, the BOP 920,and the bell nipple 918. From the bell nipple 918, the drilling fluid isdirected through a mud return line 946 to a solids removal equipment 948for removal of cuttings and release into the drilling fluid reserve pit932. Thus, the drilling fluid is continuously circulating, as shown byarrows 950 that generally indicate the direction of circulation of thedrilling fluid.

During drilling of a well, drill sounds are generated as a result of thedrill bit's engagement with rock. In operation, the drilling acousticsignals are generated when the drill bit 904 bites rocks at the bottomof a borehole 924. When drilling into different lithologies or the samelithology with different physical properties (for example, lithologytype, porosity, water saturation, permeability, presence ofhydrocarbons, presence of fractures, etc.) the generated drill soundsare distinctly different. The drill sounds (also referred to as“drilling acoustic signals) transmit upward along the drilling fluidboth inside the drill string 906 and the annulus 944.

As described in the disclosure, the apparatus 900 records and analyzesthe drilling acoustic signals on the surface. As shown in FIG. 9,acoustic sensors 952 are installed in a drilling fluid circulationsystem. For example, the acoustic sensors 952 may be coupled to the bellnipple 918, the standpipe 938, the gooseneck 942, or any combinationthereof. For example, in some embodiments, one or more acoustic sensorsmay be coupled to the bell nipple 918, one or more acoustic sensors maybe coupled to the standpipe 938, and one or more acoustic sensors may becoupled to the gooseneck 942. In other embodiments, the acoustic sensors952 may additionally or alternatively be coupled to other components ofthe drilling fluid circulation system.

Different acoustic sensors 952 may be used such as, for example,accelerometers, measurement microphones, contact microphones, andhydrophones. In some embodiments, one or more (for example, each)acoustic sensor 952 may include a built-in amplifier or may be connecteddirectly to an amplifier (not shown). In such embodiment, the drillingacoustic signals picked up by the acoustic sensors 952 may be amplifiedfirst by the amplifier before being transmitted to a data acquisitionunit (DAQ) 954.

As shown in FIG. 9, the apparatus 900 includes the data acquisition unit(DAQ) 954 which, in some embodiments, may be connected to the acousticsensors 952 via electronic cables 956. The drilling acoustic signalsreceived by the acoustic sensors 952 may be amplified and thentransmitted to the data acquisition unit 954. The data acquisition unit954 may be connected to a computer 958 through an electronic cable 960.The data acquisition unit 954 samples the acoustic signal in analogformat and then converts the analog acoustic signals into digital data(shown in FIG. 10). In some embodiments, a repeater 962 may be installedin the electronic cable 960 to relay the data from the data acquisitionunit 954 to the computer 958 if the distance between the dataacquisition unit 954 and the computer 958 exceeds a maximum specifieddistance of the electronic cable 960.

As shown in FIG. 9, the computer includes a processor 966 and a memory968 (that is, a non-transitory machine readable medium) accessible bythe processor. The memory 968 includes a computer program 970 (that is,a petrophysical properties analyzing program).

FIG. 10 depicts a data processing procedure performed by the computerprogram 970 according to an embodiment of the present disclosure. Asshown in FIGS. 9 and 10, digitized data 1000 may be read by the computerprogram 970 (for example, a petrophysical properties analyzing program),installed in memory 968 accessible by the processor 966. The computerprogram 970 analyzes the digitized data 1000 to derive a frequencydistribution 1002, acoustic characteristics 1004, and petrophysicalproperties 1006 of the rock undergoing drilling. The respective results,for example, frequency distribution 1002, acoustic characteristics 1004,and petrophysical properties 1006, can be used in various applications1008 to include lithology identification, drill bit steering, formationboundary identification, and other applications. As shown in FIG. 9,such data along with rock sample data, rock modeling data, etc. can bestored in a database 972 stored in the internal memory 968 or anexternal memory accessible to the processor 966.

The computer 958 can be in the form of a personal computer or in theform of a server or server farm serving multiple user interfaces orother configurations known to those skilled in the art. The computerprogram 970 can be in the form of microcode, programs, routines, andsymbolic languages that provide a specific set or sets of orderedoperations that control the functioning of the hardware and direct itsoperation, as known and understood by those skilled in the art. Thecomputer program 970, according to an embodiment of the presentdisclosure, need not reside in its entirety in volatile memory, but canbe selectively loaded, as necessary, according to various methodologiesas known and understood by those skilled in the art.

In operation, when the drilling acoustic signals are generated at thedrill bit 904, they transmit toward the surface through the drillingfluid 930 both inside the drill string 906 and the annulus 944. Thedrilling acoustic signals transmitted in the drilling fluid are pickedup by the acoustic sensors 952 attached to the bell nipple 918, thestandpipe 938, the gooseneck 942, other components of the drilling fluidcirculation system, or any combination thereof. The drilling acousticsignals picked up by the acoustic sensors 952, after being amplified,are sent through electronic wires 956 to the data acquisition unit (DAQ)954. The acoustic signals are digitized by the data acquisition unit 954and then sent to the computer 958 for analysis by the petrophysicalproperties analyzing program 970. The digitized acoustic signals arefirst transformed into frequency domain by using Fourier transformation.The frequency distribution data are further evaluated for acousticcharacteristics. The frequency distribution, characteristics of theacoustic signals, or both may then be used to identify lithology and toevaluate petrophysical properties of the rock under drilling in realtime, as described in the disclosure.

FIG. 10 further illustrates components of the computer program 970 inaccordance with an embodiment of the disclosure. An embodiment of thecomputer program 970 may include a data preprocess module 1010, a datasampling module 1012, an acoustic characteristics evaluation algorithm1014, and a petrophysical properties evaluation algorithm 1016. Thesampling module 1012 sends sampling commands 1018, such as samplingrate, to the data acquisition unit 954 for data sampling control. Thedata preprocess module produces filtered and restored Fast FourierTransform (FFT) data 1020 in accordance with techniques of the presentdisclosure.

FIG. 11 depicts processing by the data preprocess module 1010 inaccordance with an embodiment of the disclosure. As shown in FIG. 11,the digitized data 1000 in the time domain is transformed into FastFourier Transform (FFT) data 1102 (that is, data in the frequencydomain) by a Fast Fourier Transformation 1100. The FFT data 1102 is thenfiltered by a filter 1104 to remove some low and high frequency datapoints, low amplitude data points, or both generated from other sources,i.e. from sources other than the bit cutting into the rocks. Thefiltered FFT data 1106 is restored by the restorer 1108 to producefiltered and restored FFT data 1020. The main part of the filtered andrestored FFT data 1020 is the frequency distribution 1002, which is thefrequency and amplitude information of a sampled acoustic signal. Asdiscussed infra, two examples of such signal are shown in FIGS. 4A and4B for the frequency distribution for a limestone and the frequencydistribution for a dolomite respectively.

As the drilling acoustic signals transmit toward the surface through thedrilling fluid 930, the signals attenuate. As will be appreciated, theattenuation in a liquid generally is frequency and temperaturedependent. For example, the higher the frequency, the stronger theattenuation. As discussed in the disclosure, the attenuated drillingacoustic signals maybe restored in order to maximally represent thesounds generated by the drill bit 904. As shown in Equation 6, the soundamplitude with initial value P₀ will attenuate to a lower value P aftertransmission over a distance d:

$\begin{matrix}{P = {P_{0}10^{\frac{{- \alpha}\; d}{20}}}} & (6)\end{matrix}$

Where α is a coefficient of attenuation in decibels per meter (dB/m).

The restoration of the drilling acoustic signals may be performed byderiving the initial sounds amplitude P₀ from the measured value P at adifferent frequency, as shown by Equation 7:

$\begin{matrix}{P_{0} = {P\; 10^{\frac{\alpha \; d}{20}}}} & (7)\end{matrix}$

The attenuation in the drilling fluid may also be dependent on thedensity of the drilling fluid. For a particular drilling fluid, therelationship between the coefficients of attenuation α, the drillingfluid density ρ, sound frequencies ƒ and drilling fluid temperatures Tmay be expressed according to Equation 8:

α=function(ƒ,ρ,T,)  (8)

Equation 8 may be referred to as a “drilling fluid attenuationcoefficient function.” In some embodiments, the coefficients ofattenuation α at different the drilling fluid densities ρ, soundfrequencies ƒ, and drilling fluid temperatures T may be measured usingknown techniques. In such embodiments, the drilling fluid attenuationcoefficient function expressed by Equation 8 may be constructed from themeasurements.

The restorer 1108 of the data preprocess module 1010 may restore adrilling signal using the sounds amplitude of the filtered FFT data 1106and the drilling fluid attenuation coefficient function. To restore adrilling signal, the initial amplitude at each frequently may berestored from the filtered FFT data 1106 using Equation 7, with theattenuation coefficient determined using the drilling fluid attenuationcoefficient function expressed by Equation 8.

The filtered and restored FFT data 1020 is in the frequency domain and,as shown in FIG. 10, may include frequency distribution 1002 that isoutput from the computer program 970. The frequency distribution of thetwo different types of carbonates shown in FIGS. 4A and 4B illustratehow the frequency distribution can be used directly to identifylithologies and to determine formation boundaries during drilling realtime (that is, when drilling through a formation boundary rock lithologychanges). Identification of lithologies may be used to definehydrocarbon reservoir location and thickness, in geosteering to keepdrilling within a production zone during lateral drilling, and in otherapplications. Determination of a formation boundary in real-time mayimprove casing shoe positioning and increase drilling safety.

According to embodiments of the disclosure, the acoustic characteristicsevaluation algorithm 1014 evaluates the filtered and restored FFT data1020 for select acoustic characteristics, such as, for example, meanfrequency, normalized deviation of frequency, mean amplitude, normalizeddeviation of amplitude, and apparent power. These acousticcharacteristics for an acoustic signal sample may be defined accordingto Equations 1-5 described supra.

The mean frequency and the normalized deviation of frequencycharacterize the frequency distribution, while the mean amplitude andthe normalized deviation of amplitude characterize the loudness level ofthe drilling sound. Apparent power represents the power of the acousticsignals. In some embodiments, the acoustic characteristics may becalculated within a whole range or a partial range of the frequency ofthe acoustic samples. The range may be selected to achieve the maximumdifference of these characteristics among different lithologies.

The derived acoustic characteristics 1004 can be used directly forcertain applications 1008, such as lithology type identification orformation boundary determination. In some embodiments, the meanfrequency, the normalized deviation of frequency, the mean amplitude,the normalized deviation of amplitude, the apparent power of the rockundergoing drilling, or any combination thereof, can be compared with acorresponding mean frequency, normalized deviation of frequency, meanamplitude, normalized deviation of amplitude and apparent power of aplurality of rock samples, or any combination thereof having differentknown lithologies to determine an amount of correlation of the acousticcharacteristics associated with the rock undergoing drilling and theacoustic characteristics associated with the rock samples. The lithologytype of the rock undergoing drilling can be determined using thecorrelation. For example, the mean frequency and the normalizeddeviation of frequency for the rock undergoing drilling may be comparedwith mean frequency and normalized deviation of frequency for rocksamples having different lithologies to identify the lithology type ofthe rock undergoing drilling. In some embodiments, the location of aformation boundary may be determined in real-time from the comparison,such as by changes in lithology type of the rock undergoing drilling. Insome embodiments, the optimal location of a casing show for a casingassociated with the drill string may be determined based on the locationof the formation boundary. In some embodiments, the mean frequency, thenormalized deviation of frequency, the mean amplitude, the normalizeddeviation of amplitude, and the apparent power for the rock undergoingdrilling may be compared with the mean frequency, the normalizeddeviation of frequency, the mean amplitude, the normalized deviation ofamplitude, and the apparent power for rock samples having differentknown lithologies to identify the lithology type of the rock undergoingdrilling.

When each of the five acoustic characteristics 1004 is plotted alongdepth, each acoustic characteristic represents the property variationalong depth for the rocks in the well. Conventional well logs, such asgamma ray logs, density logs, or sonic logs and the like, may also beplotted along depth to show the lithology type and properties variationalong depth. In such embodiments, the acoustic characteristics 1004 maybe combined with the conventional well logs to enhance the evaluation oflithology type and properties.

The petrophysical properties evaluation algorithm 1016 of the computerprogram 970 evaluates the filtered and restored FFT Data 1020 to derivepetrophysical properties 1006. The petrophysical properties may includelithology types and physical properties of the rock under drilling, suchas porosity, permeability, oil presence, and fractures. In someembodiments, the location of a formation boundary may be determined inreal-time from the petrophysical properties of the rock undergoingdrilling, such as by changes in the petrophysical properties. In someembodiments, the optimal location of a casing show for a casingassociated with the drill string may be determined based on the locationof the formation boundary.

FIGS. 12 and 13 illustrate examples of the construction of two types ofpetrophysical properties evaluation algorithms 1016: one designed for aparticular type of drill bit shown at 1016A and the other designed to bedrill bit type independent shown at 1016B. Unlike the acousticcharacteristics evaluation algorithm 1014, which may be based on knownmathematical equations, the petrophysical properties evaluationalgorithm 1016 may be based on mathematical models, which are to bebuilt utilizing acoustic data and petrophysical properties according tothe techniques described in the disclosure.

FIG. 12 illustrates the procedure for constructing a “PetrophysicalProperties Evaluation Algorithm” for a particular type of drill bit.According to the exemplary configuration, datasets of petrophysicalproperties 1200 and correspondent digitized acoustic data 1202 for aparticular drill bit are collected. The digitized acoustic data 1202 ispreprocessed by the data preprocess module 1010 (illustrated in FIGS. 10and 11) to produce the filtered and restored FFT data 1204. Therelationships 1208 between filtered and restored FFT data 1204 andpetrophysical properties 1200 are constructed (step 1206) using suitablemathematical modeling techniques, such as, multiple regression analysisor artificial neural networks modeling. Once relationships 1208 betweenthe filtered and restored FFT data 1204 and petrophysical properties1200 are constructed, the relationships are coded (step 1210) to producea computer program, module, subroutine, object, or other type ofinstructions to define the petrophysical properties evaluation algorithm1016A. The algorithm 1016A is then available to be used in the computerprogram 970 to predict the petrophysical properties from drillingacoustic signals for the particular drill bit type.

FIG. 13 illustrates the procedure for constructing a drill bit typeindependent “Petrophysical Properties Evaluation Algorithm” 1016B. Thedatasets of petrophysical properties 1300 and the correspondentdigitized acoustic data 1302 measured from different types of drill bitare collected. The digitized acoustic data 1302 is preprocessed by thedata preprocess module 1010 (illustrated in FIGS. 10 and 11) to producethe filtered and restored FFT data 1304. Bit type independent features1308 of the filtered and restored FFT data 1304 are then determined bycomparing the filtered and restored FFT data of different types of drillbit and the correspondent petrophysical properties 1300 (step 1306).Features which have weakest correlation with the drill bit types andstrong correlation with the petrophysical properties are the bit-typeindependent ones. The relationships 1312 between the petrophysicalproperties 1300 and the bit type independent features 1308 areconstructed (step 1310) using suitable mathematical modeling techniques,such as, for example, multiple regression analysis or artificial neuralnetworks modeling. The constructed relationships 1312 are then coded(step 1314) into a computer program, module, subroutine, object, orother type of instructions to define the petrophysical propertiesevaluation algorithm 1016B. The algorithm 1016B is then available to beused in the computer program 970 to predict the petrophysical propertiesfrom drilling acoustic signals.

Embodiments of the apparatus 900 provide several advantages, such as theidentification of lithology type and physical properties in real-time.The advantages provided by embodiments of the apparatus 900 makes suchembodiments ideal in the applications of (1) horizontal and lateral welldrill steering and (2) locating the relative position for setting thecasing shoe at a much higher precision. Embodiments may also be used to(3) detect fractured zones; and (4) interpret rock lithologies andpetrophysical properties. Further, embodiments of the apparatus 900beneficially supply more information for evaluating petrophysicalproperties of the rocks, such as porosity, strength, and presence ofhydrocarbons, through the use of data obtained through the analysis ofacoustic signals to evaluate these petrophysical properties. Such datais beneficially beyond that which can be supplied via conventionaltechniques such as well logs.

Some embodiments of the apparatus 900 may exclude the petrophysicalproperties evaluation algorithm 1016, as the frequency distribution 1002and acoustic characteristics 1004 may be used in various applications.Such application may include identifying lithology type and formationboundaries, correlating lithology formations at different welllocations, steering lateral well drilling, etc., by comparing thefrequency distribution 1002 and acoustic characteristics 1004 of therock undergoing drilling with those collected in the upper sections ofthe well undergoing drilling (that is, an “on-the-fly” application) orfrom a database with known lithology types and petrophysical properties.

In embodiments of the disclosure, the petrophysical propertiesevaluation algorithms 1016 may be constructed easily as 1) drillingacoustic signal data used in the model construction may be easily andautomatically collected on surface; and 2) the constructed algorithms1016 may be installed in a computer on the surface.

Various embodiments of the present disclosure provide severaladvantages. For example, various embodiments of the present disclosurebeneficially provide a means to identify lithology type and physicalproperties, truly in real-time. This advantage makes various embodimentsof the present disclosure ideal in the applications of (1) horizontaland lateral well drill steering and (2) locating the relative positionfor setting the casing shoe at a much higher precision. Variousembodiments can also be used to (3) detect fractured zones; and (4)interpret rock lithologies and petrophysical properties. Variousembodiments of the present disclosure beneficially supply moreinformation for evaluating petrophysical properties of the rocks, suchas porosity, strength, and presence of hydrocarbons, through theutilization of data obtained through the analysis of acoustic signals toevaluate these petrophysical properties. Such data can beneficially bebeyond that which can be conventionally supplied.

This application is a continuation-in-part of and claims priority to andthe benefit of U.S. Non-Provisional patent application Ser. No.13/554,369 titled “Methods Of Evaluating Rock Properties While DrillingUsing Downhole Acoustic Sensors And A Downhole Broadband TransmittingSystem” filed on Jul. 20, 2012, which is a non-provisional of and claimspriority to and the benefit of U.S. Provisional Patent Application No.61/539,171, titled “Methods Of Evaluating Rock Properties While DrillingUsing Downhole Acoustic Sensors And A Downhole Broadband TransmittingSystem,” filed on Sep. 26, 2011, and is related to U.S. patentapplication Ser. No. 13/554,019, filed on Jul. 20, 2012, titled“Apparatus, Computer Readable Medium and Program Code for EvaluatingRock Properties While Drilling Using Downhole Acoustic Sensors andTelemetry System”; U.S. patent application Ser. No. 13/553,958, filed onJul. 20, 2012, titled “Methods of Evaluating Rock Properties WhileDrilling Using Downhole Acoustic Sensors and Telemetry System”; U.S.patent application Ser. No. 13/554,298, filed on Jul. 20, 2012, titled“Apparatus for Evaluating Rock Properties While Drilling Using DrillingRig-Mounted Acoustic Sensors”; and U.S. patent application Ser. No.13/554,470, filed on Jul. 20, 2012, titled “Methods for Evaluating RockProperties While Drilling Using Drilling Rig-Mounted Acoustic Sensors”;U.S. patent application Ser. No. 13/554,077, filed on Jul. 20, 2012,titled “Apparatus, Computer Readable Medium, and Program Code ForEvaluating Rock Properties While Drilling Using Downhole AcousticSensors and a Downhole Broadband Transmitting System; U.S. ProvisionalPatent Application No. 61/539,165, titled “Apparatus And Program ProductFor Evaluating Rock Properties While Drilling Using Downhole AcousticSensors And A Downhole Broadband Transmitting System,” filed on Sep. 26,2011; U.S. Provisional Patent Application No. 61/539,201, titled“Apparatus For Evaluating Rock Properties While Drilling Using DrillingRig-Mounted Acoustic Sensors,” filed on Sep. 26, 2011; U.S. ProvisionalPatent Application No. 61/539,213, titled “Methods For Evaluating RockProperties While Drilling Using Drilling Rig-Mounted Acoustic Sensors,”filed on Sep. 26, 2011; U.S. Provisional Patent Application No.61/539,242 titled “Apparatus And Program Product For Evaluating RockProperties While Drilling Using Downhole Acoustic Sensors And TelemetrySystem,” filed on Sep. 26, 2011; and U.S. Provisional Patent ApplicationNo. 61/539,246 titled “Methods Of Evaluating Rock Properties WhileDrilling Using Downhole Acoustic Sensors And Telemetry System,” filed onSep. 26, 2011, each incorporated herein by reference in its entirety.

In the drawings and specification, there have been disclosed a typicalpreferred embodiment of the invention, and although specific terms areemployed, the terms are used in a descriptive sense only and not forpurposes of limitation. The invention has been described in considerabledetail with specific reference to these illustrated embodiments. It willbe apparent, however, that various modifications and changes can be madewithin the spirit and scope of the invention as described in theforegoing specification.

That claimed is:
 1. An apparatus for determining properties of rock in aformation in real-time during drilling, the apparatus comprising: anacoustic sensor installed in a drilling fluid circulation system of adrilling rig, the acoustic sensor coupled to one of the following: (i) abell nipple, (ii) a gooseneck, or (iii) a standpipe, wherein theacoustic sensor is operable to detect an acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling and transmitted through the drilling fluid; a dataacquisition unit in communication with the acoustic sensor and acomputer, wherein the data acquisition unit is operable to sample theraw acoustic sensor data and digitize the raw acoustic sensor data, theraw acoustic sensor data representing the acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling; the computer in communication with the data acquisitionunit and configured to perform the following operations: receiving thedigitized acoustic sensor data from the data acquisition unit;processing the digitized acoustic sensor data received from the dataacquisition unit, the processing comprising: deriving a plurality ofacoustic characteristics from the digitized acoustic sensor data, theplurality of acoustic characteristics including mean frequency andnormalized deviation of frequency; and comparing the mean frequency andthe normalized deviation of frequency for the rock undergoing drillingwith mean frequency and normalized deviation of frequency for aplurality of rock samples having different known lithologies;identifying a lithology type of the rock undergoing drilling responsiveto the comparing.
 2. The apparatus of claim 1, wherein the plurality ofacoustic characteristics further include mean amplitude, normalizeddeviation of amplitude, and apparent power, wherein the operationscomprise: comparing the mean frequency, the normalized deviation offrequency, the mean amplitude, and the normalized deviation ofamplitude, and the apparent power for the rock undergoing drilling withmean frequency, normalized deviation of frequency, mean amplitude,normalized deviation of amplitude, and apparent power for a plurality ofrock samples having different known lithologies.
 3. The apparatus ofclaim 1, wherein the processing comprises: sending sampling commands tothe data acquisition unit in communication with the one or more acousticsensors; converting analog acoustic signals into digitized data throughemployment of the data acquisition unit; transforming the digitized datainto Fast Fourier Transform (FFT) data using a Fast Fouriertransformation; filtering the FFT data; restoring the FFT data tocompensate for attenuation by the drilling fluid; deriving the pluralityof acoustic characteristics from the filtered and restored Fast FourierTransform data.
 4. The apparatus of claim 1, comprising an amplifierconnected to the acoustic sensor, wherein the amplifier is operable toamplify the raw acoustic sensor data before being received by the dataacquisition unit.
 5. The apparatus of claim 1, wherein the acousticsensor comprises a first acoustic sensor coupled to the bell nipple ofthe drilling fluid circulation system.
 6. The apparatus of claim 5,wherein the acoustic sensor comprises a second acoustic sensor coupledto the gooseneck of the drilling fluid circulation system.
 7. Theapparatus of claim 6, wherein the acoustic sensor comprises a thirdacoustic sensor coupled to the standpipe of the drilling fluidcirculation system.
 8. An apparatus for determining properties of rockin a formation in real-time during drilling, the apparatus comprising:an acoustic sensor installed in a drilling fluid circulation system of adrilling rig, the acoustic sensor coupled to one of the following: (i) abell nipple, (ii) a gooseneck, or (iii) a standpipe, wherein theacoustic sensor is operable to detect an acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling and transmitted through the drilling fluid; a dataacquisition unit in communication with the acoustic sensor and acomputer, wherein the data acquisition unit is operable to sample theraw acoustic sensor data and digitize the raw acoustic sensor data, theraw acoustic sensor data representing the acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling; the computer in communication with the data acquisitionunit and configured to perform the following operations: receivingdigitized acoustic sensor data from the data acquisition unit, the rawacoustic sensor data representing the acoustic signal generatedreal-time as a result of rotational contact of a drill bit with rockduring drilling; processing the raw acoustic sensor data received fromthe acoustic sensor, the processing comprising: transforming thedigitized data into Fast Fourier Transform (FFT) data using a FastFourier transformation; filtering the FFT data; and restoring the FFTdata to compensate for attenuation by the drilling fluid; determiningpetrophysical properties of rock being encountered by the drill bitusing a petrophysical properties evaluation algorithm employable topredict one or more petrophysical properties of rock undergoing drillingfrom the filtered and restored FFT data.
 9. The apparatus of claim 8,comprising an amplifier connected to the acoustic sensor, wherein theamplifier is operable to amplify the raw acoustic sensor data beforebeing received by the data acquisition unit.
 10. The apparatus of claim8, wherein the processing comprises: sending sampling commands to thedata acquisition unit in communication with the one or more acousticsensors; converting analog acoustic signals into digitized data throughemployment of the data acquisition unit.
 11. The apparatus of claim 8,wherein the one or more petrophysical properties comprise: lithologytype, porosity, water saturation, and permeability of rock undergoingdrilling.
 12. The apparatus of claim 8, wherein the petrophysicalproperties evaluation algorithm is a bit-specific petrophysicalproperties evaluation algorithm, the processing comprising: collectingpetrophysical properties data describing one or more petrophysicalproperties of rock and correspondent acoustic data for a preselectedtype of drill bit; processing the collected acoustic data to producefiltered and restored FFT data; determining one or more relationshipsbetween features of the filtered and restored FFT data and correspondentone or more petrophysical properties of rock for each type of drill bit;coding the determined relationships into computer program code definingthe petrophysical properties algorithm.
 13. The apparatus of claim 8,wherein the petrophysical properties evaluation algorithm is abit-independent petrophysical properties evaluation algorithm, theprocessing comprising: collecting petrophysical properties datadescribing one or more petrophysical properties of rock andcorrespondent acoustic data for a plurality of different types of drillbits; processing the collected acoustic data to produce filtered andrestored FFT data; determining bit-type independent features of thefiltered and restored FFT data; determining one or more relationshipsbetween the bit-type independent features of the filtered and restoredFFT data and correspondent one or more petrophysical properties of therock; and coding the determined relationships into computer program codedefining the petrophysical properties algorithm.
 14. The apparatus ofclaim 8, wherein the acoustic sensor comprises a first acoustic sensorcoupled to the bell nipple of the drilling fluid circulation system. 15.The apparatus of claim 14, wherein the acoustic sensor comprises asecond acoustic sensor coupled to the gooseneck of the drilling fluidcirculation system.
 16. The apparatus of claim 15, wherein the acousticsensor comprises a third acoustic sensor coupled to the standpipe of thedrilling fluid circulation system.
 17. A method for determiningproperties of rock in a formation in real-time during drilling using adrilling fluid, the method comprising: detecting, by an acoustic sensor,an acoustic signal generated real-time as a result of rotational contactof a drill bit with rock during drilling and transmitted through thedrilling fluid, the acoustic sensor installed in a drilling fluidcirculation system of a drilling rig, and coupled to one of thefollowing: (i) a bell nipple, (ii) a gooseneck, or (iii) a standpipe;digitizing, by a data acquisition unit, the raw acoustic sensor data;processing, at a computer in communication with the data acquisitionunit, the digitized acoustic sensor data received from the dataacquisition unit, the processing comprising: deriving a plurality ofacoustic characteristics from the digitized acoustic sensor data, theplurality of acoustic characteristics including mean frequency andnormalized deviation of frequency; and comparing the mean frequency andthe normalized deviation of frequency for the rock undergoing drillingwith mean frequency and normalized deviation of frequency for aplurality of rock samples having different known lithologies; andidentifying a lithology type of the rock undergoing drilling responsiveto the comparing.
 18. The method of claim 17, wherein the processingcomprises: sending sampling commands to the data acquisition unit incommunication with the one or more acoustic sensors; converting analogacoustic signals into digitized data through employment of the dataacquisition unit; transforming the digitized data into Fast FourierTransform (FFT) data using a Fast Fourier transformation; filtering theFFT data; restoring the FFT data to compensate for attenuation by thedrilling fluid; deriving the plurality of acoustic characteristics fromthe filtered and restored FFT data.
 19. The method of claim 17,comprising amplifying the raw acoustic sensor data by an amplifierbefore being received by the data acquisition unit.
 20. The method ofclaim 17, wherein the plurality of acoustic characteristics furtherinclude mean amplitude, normalized deviation of amplitude, and apparentpower, wherein the method comprises: comparing the mean frequency, thenormalized deviation of frequency, the mean amplitude, the normalizeddeviation of amplitude, and the apparent power for the rock undergoingdrilling with mean frequency, normalized deviation of frequency, meanamplitude, normalized deviation of amplitude, and apparent power for aplurality of rock samples having different known lithologies
 21. Themethod of claim 17, comprising determining a location of a formationboundary encountered during drilling responsive to the comparing. 22.The method of claim 21, comprising determining an optimal location of acasing shoe for a casing associated with a drill string based on thelocation of the formation boundary.
 23. The method of claim 17, whereinthe acoustic sensor comprises a first acoustic sensor coupled to thebell nipple of the drilling fluid circulation system.
 24. The method ofclaim 23, wherein the acoustic sensor comprises a second acoustic sensorcoupled to the gooseneck of the drilling fluid circulation system. 25.The method of claim 24, wherein the acoustic sensor comprises a thirdacoustic sensor coupled to the standpipe of the drilling fluidcirculation system.
 26. A method for determining properties of rock in aformation in real-time during drilling using a drilling fluid, themethod comprising: detecting, by an acoustic sensor, an acoustic signalgenerated real-time as a result of rotational contact of a drill bitwith rock during drilling and transmitted through the drilling fluid,the acoustic sensor installed in a drilling fluid circulation system ofa drilling rig, and coupled to one of the following: (i) a bell nipple,(ii) a gooseneck, or (iii) a standpipe; digitizing, by a dataacquisition unit, the raw acoustic sensor data; processing, at acomputer in communication with the data acquisition unit, the digitizedacoustic sensor data received from the data acquisition unit, theprocessing comprising: transforming the digitized data into Fast FourierTransform (FFT) data using a Fast Fourier transformation; filtering theFFT data; and restoring the FFT data to compensate for attenuation bythe drilling fluid; determining petrophysical properties of rock beingencountered by the drill bit using a petrophysical properties evaluationalgorithm employable to predict one or more petrophysical properties ofrock undergoing drilling from the filtered and restored FFT data. 27.The method of claim 26, comprising amplifying the raw acoustic sensordata by an amplifier before being received by the data acquisition unit.28. The method of claim 26, wherein the one or more petrophysicalproperties comprise: lithology type, porosity, water saturation, andpermeability of rock undergoing drilling.
 29. The method of claim 26,wherein the petrophysical properties evaluation algorithm is abit-specific petrophysical properties evaluation algorithm, the methodcomprising: collecting petrophysical properties data describing one ormore petrophysical properties of rock and correspondent acoustic datafor a preselected type of drill bit; processing the collected acousticdata to produce filtered and restored FFT data; determining one or morerelationships between features of the filtered and restored FFT data andcorrespondent one or more petrophysical properties of rock for each typeof drill bit; coding the determined relationships into computer programcode defining the petrophysical properties algorithm.
 30. The method ofclaim 26, wherein the petrophysical properties evaluation algorithm is abit-independent petrophysical properties evaluation algorithm, themethod comprising: collecting petrophysical properties data describingone or more petrophysical properties of rock and correspondent acousticdata for a plurality of different types of drill bits; processing thecollected acoustic data to produce filtered and restored FFT data;determining bit-type independent features of the filtered and restoredFFT data; determining one or more relationships between the bit-typeindependent features of the filtered and restored FFT data andcorrespondent one or more petrophysical properties of the rock; andcoding the determined relationships into computer program code definingthe petrophysical properties algorithm.
 31. The method of claim 26,comprising determining a location of a formation boundary encounteredduring drilling based on the determined petrophysical properties of therock undergoing drilling.
 32. The method of claim 31, comprisingdetermining an optimal location of a casing shoe for a casing associatedwith a drill string based on the location of the formation boundary. 33.The method of claim 26, wherein the acoustic sensor comprises a firstacoustic sensor coupled to the bell nipple of the drilling fluidcirculation system.
 34. The method of claim 26, wherein the acousticsensor comprises a second acoustic sensor coupled to the gooseneck ofthe drilling fluid circulation system.
 35. The method of claim 26,wherein the acoustic sensor comprises a third acoustic sensor coupled tothe standpipe of the drilling fluid circulation system.